Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
breaks: list<item: struct<left_context: string, text_break_string: string, contextual_break_string: string, (... 20 chars omitted)
child 0, item: struct<left_context: string, text_break_string: string, contextual_break_string: string, char_offset (... 8 chars omitted)
child 0, left_context: string
child 1, text_break_string: string
child 2, contextual_break_string: string
child 3, char_offset: int64
multiple: bool
multiple_count: int64
label_format: struct<breaks: list<item: struct<left_context: string, text_break_string: string, contextual_break_s (... 55 chars omitted)
child 0, breaks: list<item: struct<left_context: string, text_break_string: string, contextual_break_string: string, (... 21 chars omitted)
child 0, item: struct<left_context: string, text_break_string: string, contextual_break_string: string, char_offset (... 9 chars omitted)
child 0, left_context: string
child 1, text_break_string: string
child 2, contextual_break_string: string
child 3, char_offset: string
child 1, multiple: string
single_count: int64
single: list<item: struct<file: string, w_id: string, volume: int64, i_id: string, img_num: int64, start_cou (... 77 chars omitted)
child 0, item: struct<file: string, w_id: string, volume: int64, i_id: string, img_num: int64, start_count: int64, (... 65 chars omitted)
child 0, file: string
child 1, w_id: string
child 2, volume: int64
child 3, i_id: string
child 4, img_num: int64
child 5, start_count: int64
child 6, segment_ids: list<item: string>
child 0, item: string
child 7, n_breaks: int64
child 8, multiple: bool
source: string
to
{'single_count': Value('int64'), 'multiple_count': Value('int64'), 'source': Value('string'), 'label_format': {'breaks': List({'left_context': Value('string'), 'text_break_string': Value('string'), 'contextual_break_string': Value('string'), 'char_offset': Value('string')}), 'multiple': Value('string')}, 'single': List({'file': Value('string'), 'w_id': Value('string'), 'volume': Value('int64'), 'i_id': Value('string'), 'img_num': Value('int64'), 'start_count': Value('int64'), 'segment_ids': List(Value('string')), 'n_breaks': Value('int64'), 'multiple': Value('bool')}), 'multiple': List({'file': Value('string'), 'w_id': Value('string'), 'volume': Value('int64'), 'i_id': Value('string'), 'img_num': Value('int64'), 'start_count': Value('int64'), 'segment_ids': List(Value('string')), 'n_breaks': Value('int64'), 'multiple': Value('bool')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
breaks: list<item: struct<left_context: string, text_break_string: string, contextual_break_string: string, (... 20 chars omitted)
child 0, item: struct<left_context: string, text_break_string: string, contextual_break_string: string, char_offset (... 8 chars omitted)
child 0, left_context: string
child 1, text_break_string: string
child 2, contextual_break_string: string
child 3, char_offset: int64
multiple: bool
multiple_count: int64
label_format: struct<breaks: list<item: struct<left_context: string, text_break_string: string, contextual_break_s (... 55 chars omitted)
child 0, breaks: list<item: struct<left_context: string, text_break_string: string, contextual_break_string: string, (... 21 chars omitted)
child 0, item: struct<left_context: string, text_break_string: string, contextual_break_string: string, char_offset (... 9 chars omitted)
child 0, left_context: string
child 1, text_break_string: string
child 2, contextual_break_string: string
child 3, char_offset: string
child 1, multiple: string
single_count: int64
single: list<item: struct<file: string, w_id: string, volume: int64, i_id: string, img_num: int64, start_cou (... 77 chars omitted)
child 0, item: struct<file: string, w_id: string, volume: int64, i_id: string, img_num: int64, start_count: int64, (... 65 chars omitted)
child 0, file: string
child 1, w_id: string
child 2, volume: int64
child 3, i_id: string
child 4, img_num: int64
child 5, start_count: int64
child 6, segment_ids: list<item: string>
child 0, item: string
child 7, n_breaks: int64
child 8, multiple: bool
source: string
to
{'single_count': Value('int64'), 'multiple_count': Value('int64'), 'source': Value('string'), 'label_format': {'breaks': List({'left_context': Value('string'), 'text_break_string': Value('string'), 'contextual_break_string': Value('string'), 'char_offset': Value('string')}), 'multiple': Value('string')}, 'single': List({'file': Value('string'), 'w_id': Value('string'), 'volume': Value('int64'), 'i_id': Value('string'), 'img_num': Value('int64'), 'start_count': Value('int64'), 'segment_ids': List(Value('string')), 'n_breaks': Value('int64'), 'multiple': Value('bool')}), 'multiple': List({'file': Value('string'), 'w_id': Value('string'), 'volume': Value('int64'), 'i_id': Value('string'), 'img_num': Value('int64'), 'start_count': Value('int64'), 'segment_ids': List(Value('string')), 'n_breaks': Value('int64'), 'multiple': Value('bool')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Page-overlap benchmark
This benchmark dataset for detecitng the text boundaries in page where text boundaires overlap while transferring BDRC page-level outlines into character-level outlines over OCR text.
Most outlined texts line up with page boundaries. For those cases the character span is the first character of the start page through the last character of the end page. Some texts do not: one work can end mid-page while another begins on the same page, or several short works can start and end on one page (one text ends, the next occupies only a few lines, then another begins).
To locate those mid-page boundaries we compare a rule-based finder, an LLM (Gemini), and a custom fine-tuned mmBERT boundary detector. This benchmark measures which method recovers the gold offsets more accurately.
Dataset
96 OCR pages from 77 works & 77 scan volumes, split evenly by overlap type:
- 48 single-overlap pages — two texts share the page (
multiple: false, one break) - 48 multiple-overlap pages — three or more texts share the page (
multiple: true, two or more breaks)
Together the gold labels contain 149 text breaks. Pages come from real overlapping OCR, not synthetic splits.
page_benchmark/
single/page1.txt
single/page1.json
…
multiple/page1.txt
multiple/page1.json
manifest.json
pageN.json looks like:
{
"breaks": [
{
"left_context": "དགེ་བར་གྱུར་ཅིག།",
"text_break_string": " །། ༄། །",
"contextual_break_string": "དགེ་བར་གྱུར་ཅིག། །། ༄། །",
"char_offset": 291
}
],
"multiple": false
}
char_offsetis the exclusive page-local end of the ending work's terminal markermanifest.jsonhasw_id, volume,i_id, image number, and outline segment ids
license: cc
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